CVE-2022-35989: `CHECK` fail in `MaxPool` in TensorFlow

Published Sep 16, 2022
·
Updated

TensorFlow is an open source platform for machine learning. When MaxPool receives a window size input array ksize with dimensions greater than its input tensor input, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Affected Software

7 affected components
Google TensorFlow<2.7.2
Google TensorFlow>=2.8.0<2.8.1
Google TensorFlow>=2.9.0<2.9.1
Google TensorFlow=2.10-rc0
Google TensorFlow=2.10-rc1
Google TensorFlow=2.10-rc2
Google TensorFlow=2.10-rc3

Event History

Sep 16, 2022
CVE Published
via MITRE·09:35 PM
Data Sourced
via MITRE·09:35 PM
DescriptionSeverityWeakness

Frequently Asked Questions

1

What is the severity of CVE-2022-35989?

CVE-2022-35989 is classified as a denial of service vulnerability.

2

How do I fix CVE-2022-35989?

To fix CVE-2022-35989, upgrade TensorFlow to the latest version that addresses this vulnerability.

3

What versions of TensorFlow are affected by CVE-2022-35989?

TensorFlow versions up to 2.7.2 and those from 2.8.0 to 2.8.1, 2.9.0 to 2.9.1, and pre-release versions 2.10-rc0 to 2.10-rc3 are affected.

4

What causes the issue in CVE-2022-35989?

CVE-2022-35989 occurs when the MaxPool operation receives an input size that exceeds the dimensions of its input tensor.

5

Is there a workaround for CVE-2022-35989?

There is no specified workaround for CVE-2022-35989; upgrading TensorFlow is recommended to mitigate the risk.

Contact

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